10 years’ experience in EEG task design, analysis, lab management, training, support and consultancy.
Originally based in the North East of England, Dr A.J Hanson, completed a BSc Honours degree in Physiological Sciences before undertaking a PhD in Computational Neuroscience as a member of staff at the Institute of Neuroscience, Newcastle University. In his role as the sole EEG technologist for the University, he has supported the work of staff and students since 2007; developing in-house experimental presentation scripts and custom analysis strategies, installing and maintaining hardware and software across a multi-site setting, and delivering hands-on training and data collection for numerous research teams across a broad-range of neuroscience disciplines. Later in his career his skills started to be called upon by research groups outside of Newcastle University, performing analytical services, training and consultancy for research teams in York, Oxford, Cambridge, Lisbon and Leipzig Universities. In a move to further develop the level of support that he could provide to the global research community, TheNeuroTechnologist.com was launched in 2018, to ensure that all students, academics and private companies had a means by which to access experienced technical assistance and services that would typically only be available via an in-house EEG technologist. Furthermore, TheNeuroTechnologist.com aims to become and indispensable resource for all current and future EEG technologists and researchers; listing current developments in hardware, software and analysis strategies, training opportunities, conference listings, code repositories, technical manuals, and general advice.
Neuroscan School (Charlotte, NC)
EEGLab Workshop (Aspet, France)
CuttingEEG Conference and Workshops (Glasgow, UK)
Deleveloping skills and knowledge of cross-modal EEG systems and analysis strategies (i.e. EEG combined with fMRI, fNIRS, TCS or TMS).
PhD Research Focus
“Event-related EEG analysis: Simple solutions or complex computations”
Independently developed a semi-automated EEG analysis pipeline using a variety of EEGLab-based funcation and novel data exclusion methodologies to assess the real-world benefits of various artefact rejection strategies and signal isolation techniques.